Measuring Digitalization

A sociotechnical KPI model for the digital transformation

JournalIndustrie 4.0 Management
Issue Volume 37, 2021, Edition 3, Pages 30-34
Open Accesshttps://doi.org/10.30844/I40M_21-3_S30-34
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Abstract

A successful digital transformation for attaining Industry 4.0, is a crucial success criterion for many companies today. The ongoing global COVID-19 pandemic has shown the need for digitalization in companies and has further accelerated this development. However, these times, companies are confronted with an uncertain order and profit situation. Thus, they need to allocate their investments purposefully. Evaluating the digital maturity by using a profound indicator system is therefore a sound basis for decision making. This paper develops such a sociotechnical KPI model along the dimensions “Strategy and Organizational Leadership”, “Digital Skills/Human Capital” as well as “Smart Process/Operations”. In the future, this model can be used for determining the digital maturity and thus, it can be applied for allocating digitalization investments.

Keywords


Bibliography

[1] Zimmermann, V.: KfW-Digitalisierungsbericht Mittelstand 2019. Digitalisierungsprojekte zunehmend im Mittelstand verbreitet, Digitalisierungsausgaben jedoch seit Jahren unverändert niedrig. Frankfurt am Main 2020.
[2] Kersten, W.; von See, B.; Lodemann, S.; Grotemeier, C.: Trends und Strategien in Logistik und Supply Chain Management. Entwicklungen und Perspektiven einer nachhaltigen und digitalen Transformation. Bremen 2020.
[3] Brink, S.; Levering, B.; Icks, A.: Herausforderungen des deutschen Mittelstands in der Corona-Pandemie. Sonderauswertung des Zukunftspanel Mittelstand 2020. Bonn 2020.
[4] Wrobel, M.; Schildhauer, T.; Preiß, K.: Kooperation zwischen Startups und Mittelstand. Learn. Match. Partner. Berlin 2017.
[5] Nielen, S.; Kay, R.; Schröder, C.: Disruptive Innovationen: Chancen und Risiken für den Mittelstand. Bonn 2017.
[6] Leyh, C.; Bley, K.: Digitalisierung: Chance oder Risiko für den deutschen Mittelstand? – Eine Studie ausgewählter Unternehmen. In: HMD Praxis der Wirtschaftsinformatik 53 (2016) 1, S. 29–41.
[7] Franceschini, F.; Galetto, M.; Maisano, D.; Neely, A. D.: Designing performance measurement systems. Theory and practice of key performance indicators. Cham 2019.
[8] Fink, A.: Conducting research literature reviews. From the internet to paper, Fourth edition. Thousand Oaks, California 2014.
[9] Krol, F.; Saeed, M. A.; Kersten, W.: A holistic digitalization KPI framework for the aerospace industry. In: Kersten, W.; Blecker, T.; Ringle, C. M. (Hrsg.): Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science and Innovation in Supply Chain Management. How Data Transforms the Value Chain. Berlin 2020.
[10]Kontić, L.; Vidicki, Đ.: Strategy for digital organization: Testing a measurement tool for digital transformation. In: Strategic Management 23 (2018) 2, S. 29–35.
[11] von See, B.; Kersten, W.: Arbeiten im Zeitalter des Internets der Dinge. Wie Qualifikation, Organisation und Führung digital transformiert werden. In: Industrie 4.0 Management 34 (2018) 3, S. 8–12.
[12]Porfírio, J. A.; Carrilho, T.; Felício, J. A.; Jardim, J.: Leadership characteristics and digital transformation. In: Journal of Business Research 124 (2021), S. 610–19.
[13]Berghaus, S.; Back, A.; Kaltenrieder, B.: Digital Maturity & Transformation Report 2017. St. Gallen 2017.
[14] Lichtblau, K.; Stich, V.; Bertenrath, R.; Blum, M.; Bleider, M.; Millac, A.; Schmitt, K.; Schmitz, E.; Schroeter, M.: Industrie 4.0 Readiness. Aachen, Cologne 2015.
[15]Waspodo, B.; Ratnawati, S.; Halifi, R.: Building Digital Strategy Plan at CV Anugrah Prima, an Information Technology Service Company: The 6th International Conference on Cyber and IT Service Management (CITSM 2018) 2018.
[16]Azhari, P.; Faraby, N.; Rossmann, A.; Steimel, B.; Wichman, K. S.: Digital Transformation Report. Köln 2014.
[17]Deloitte: Digital Maturity Model. Achieving digital maturity to drive growth. New York 2018.
[18]BSP Business School Berlin: Mitelstand im Wandel – Wie ein Unternehmen seinen digitalen Reifegrad ermitteln kann. Berlin 2016.
[19]KPMG: Digital Readiness Assessment. Berlin 2016.
[20]Buhse, W.: Management by Internet. Neue Führungsmodelle für Unternehmen in Zeiten der digitalen Transformation; Unternehmen im Wandel, digitale Medien als Werkzeugkoffer für Veränderer, Vernetzung, Offenheit, Partizipation und Agilität als Werte einer neuen Unternehmenskultur. Kulmbach 2014.
[21] EFQM: EFQM Excellence Modell. Brussels 2012.
[22] Stowasser, S.; Peschl, A.: Arbeitswelt im Wandel: Qualifizierung zu resilienzfördernder Führung. In: Spath, D.; Spanner-Ulmer, B. (Hrsg.): Digitale Transformation – Gutes Arbeiten und Qualifizierung aktiv gestalten. Berlin 2019.
[23]Geissbauer, R.; Vedso, J.; Schrauf, S.: Industry 4.0: Building the digital enterprise 2016.
[24]Kersten, W.; Seiter, M.; See, B. von; Hackius, N.; Maurer, T.: Chancen der digitalen Transformation. Trends und Strategien in Logistik und Supply Chain Management. Hamburg 2017.
[25] European Commission: The Digital Economy and Societyx Index (DESI). Integration of Digital Technology. URL: https://ec.europa.eu/ newsroom/dae/document. cfm?doc_id=59979. Abrufdatum 08.04.2020.
[26] Schumacher, A.; Erol, S.; Sihn, W.: A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. In: Procedia CIRP 52 (2016), S. 161–66.
[27]Kotarba, M.: Measuring Digitalization – Key Metrics. In: Foundations of Management 9 (2017), S. 123–38. [28]Dombrowski, U.; Wullbrandt, J.; Fochler, S.: Kompetenzentwicklung in der digitalen Transformation: dezentrales und lebenslanges Lernen im Arbeitsprozess. In: Spath, D.; Spanner-Ulmer, B. (Hrsg.): Digitale Transformation – Gutes Arbeiten und Qualifizierung aktiv gestalten. Berlin 2019.

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